# Resource Library

#### Statistical Topic

Advanced Search | Displaying 41 - 50 of 196
• ### Analysis Tool: Analysis of Covariance Model (two-way)

These pages will perform a factorial analysis of covariance for RxC independent samples, cross-tabulated according to two independent variables, A and B, where A is the row variable and B the column variable; DV = the dependent variable of interest; and CV = the concomitant variable whose effects one wishes to bring under statistical control. As the pages open, you will be prompted to enter the size of the largest of your several samples.

• ### Analysis Tool: Normal Distribution

Generate a graphic and numerical display of the properties of the Normal Distribution. For a unit normal distribution, with M=0 and SD=Œ±1, enter 0 and 1 at the prompt. For a distribution with M=100 and SD=Œ±15, enter 100 and 15. And so forth

• ### Analysis Tool: Chi-Square, Cramer's V, and Lambda for an RxC Contingency Table

This calculator performs the following for a contingency table up to 5x5: chi-square analysis; Cramer's V; two asymmetrical versions of lambda; the Goodman-Kruskal index of predictive association; other measures relevant to categorical prediction. Key Word: Categorical Analysis.

• ### Analysis Tool: First-Order Partial Correlation (For Three Intercorrelated Variables)

Given three overlapping correlation coefficients: rXY, rXZ, and rYZ, this page will calculate the first-order partial correlations: rXY.Z, rXZ.Y, and rYZ.X. If you enter the value of N (providing N>6), the program will also calculate the values of t for the partial correlations (df=N-3) along with the associated two-tailed probability values.

• ### Analysis Tool: First- and Second-Order Partial Correlations (For Four Intercorrelated Variables)

This page will calculate the first- and second-order partial correlations for four intercorrelated variables, W, X, Y, and Z. If you enter a value of N (providing N>9), the program will also calculate the values of t along with the associated two-tailed probability values.

• ### Analysis Tool: Chi-Square "Goodness of Fit"

This page will calculate the value of chi-square for a one- dimensional "goodness of fit" test, for up to 8 mutually exclusive categories labeled A through H. To enter an observed cell frequency, click the cursor into the appropriate cell, then type in the value. Expected values can be entered as either frequencies or proportions. Toward the bottom of the page is an option for estimating the relevant probability via Monte Carlo simulation of the multinomial sampling distribution.

• ### Analysis Tool: Pascal (Negative Binomial) Probabilities (For Sequential Sampling)

For a situation in which independent binomial events are randomly sampled in sequence, this page will calculate (a) the probability that you will end up with exactly k instances of the outcome in question, with the final (kth) instance occurring on trial N; and (b) the probability that you will have to sample at least N events before finding the kth instance of the outcome.

• ### Analysis Tool: Point Biserial Correlation Coefficient

This page calculates the point biserial correlation coefficient for the case where one variable is dichotomous and the other is non-dichotomous. This page allows the user to input the data directly or copy and paste from a spreadsheet application and provides data summary.

• ### Analysis Tool: Log-Linear Analysis for an AxBxC Contingency Table

Log-linear analysis is a version of chi-square analysis in which the relevant values are calculated by way of weighted natural logarithms. This page will calculate several values of G^2.

• ### Analysis Tool: 2x2x2 Analysis of Variance for Independent Samples

This page will perform an analysis of variance for the situation where there are three independent variables, A, B, and C, each with two levels. The user may enter data directly or copy and paste from a spreadsheet or other application.